{"id":"W3022402851","doi":"10.1093/neuros/nyaa168","title":"Letter: Twinkle, Twinkle Little STAR, How I Wonder What You Are: The Case for High-Quality, Large-Scale, “Real-World” Databases","year":2020,"lang":"en","type":"letter","venue":"Neurosurgery","topic":"Acute Ischemic Stroke Management","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Quality (philosophy); Scale (ratio); Randomized controlled trial; Surgery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02867911,0.0007135909,0.003042863,0.0030323,0.00239919,0.008284712,0.004957291,0.02360274,0.008364974],"category_scores_gemma":[0.3101186,0.001013239,0.001141017,0.002996493,0.005009346,0.01164685,0.002423656,0.02589553,0.005744083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002802491,"about_ca_system_score_gemma":0.00642986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002054303,"about_ca_topic_score_gemma":0.002563168,"domain_scores_codex":[0.9756771,0.01019375,0.005388174,0.002474451,0.005508906,0.0007576412],"domain_scores_gemma":[0.7149319,0.1954836,0.01534901,0.008513172,0.05480009,0.01092212],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004549184,0.0000102025,0.0006910267,0.0003188633,0.00005056618,0.0006693759,0.000141295,0.00003437633,0.00003804696,0.00118935,0.9865555,0.01025604],"study_design_scores_gemma":[0.0002090166,0.00006866955,0.001977494,0.003838082,0.0001640081,0.0071389,0.001209308,0.0007242282,0.0002917508,0.01731769,0.9668347,0.0002261604],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0002807513,0.003330824,0.0003593649,0.9672582,0.02806502,0.00001716335,0.0001564298,0.00005531142,0.000476794],"genre_scores_gemma":[0.004458568,0.006987212,0.001387705,0.8482011,0.1371359,0.00009341028,0.0001402977,0.0001060887,0.001489664],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02867911,"threshold_uncertainty_score":0.1516715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05760108979134689,"score_gpt":0.2998406200868272,"score_spread":0.2422395302954803,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}